title: Unsupervised segmentation of brain regions with similar microstructural properties: application to alcoholism.
abstract: In this work, a novel brain MRI segmentation approach evaluates microstructural differences between groups. Going further from the traditional segmentation of brain tissues (white matter -WM-, gray matter -GM- and cerebrospinal fluid -CSF- or a mixture of them), a new way to classify brain areas is proposed using their microstructural MR properties. Eight rats were studied using the proposed methodology identifying regions which present microstructural differences as a consequence on one month of hard alcohol consumption. Differences in relaxation times of the tissues have been found in different brain regions (p<0.05). Furthermore, these changes allowed the automatic classification of the animals based on their drinking history (hit rate of 93.75 % of the cases).
authors.forename: Alejandro
authors.initials: A
authors.lastname: Cosa
authors.forename: Santiago
authors.initials: S
authors.lastname: Canals
authors.forename: Ana
authors.initials: A
authors.lastname: Valles-Lluch
authors.forename: David
authors.initials: D
authors.lastname: Moratal
mesh_terms: D000437:Alcoholism / Q000473:pathology*; D000818:Animals; D001499:Bayes Theorem; D001921:Brain / Q000473:pathology*; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D051381:Rats